The associations between physical-test performance and match performance in women’s Rugby Sevens players

Evaluating the relationships between physical-test and match performance in team sports could be useful for training prescription and athlete evaluation. Here we investigated these relationships in women’s Rugby Sevens. Thirty provincial-representative players performed Bronco-fitness, countermovement-jump, acceleration, speed, and strength tests within two weeks before a two-day tournament. Match-running and match-action performance measures were provided by GPS units and video analysis. Generalised and general linear mixed models were employed to estimate the effect of a two standard-deviation difference in physical-test measures on match measures. Effect magnitudes were assessed via standardisation (using the between-player SD) and, for effects on tries scored, also via match winning (based on simulating matches). Evidence for substantial and trivial true magnitudes was provided by one-sided interval-hypothesis tests and Bayesian analysis. There was good evidence of positive effects of many physical-test measures on match high-intensity running, with large effects for jump height and acceleration. There was some evidence of small-moderate positive effects of speed and Bronco, and of small-moderate negative effects of maximal strength and jump height, on match total running and high intensity changes in speed. The evidence was generally inadequate for associations between physical-test measures and match actions, but there was good evidence of small-large positive effects of back squat and jump height on tries scored. Enhancing players’ jump height and back-squat performance might therefore increase the likelihood of match success in women’s Rugby Sevens.


INTRODUCTION
Women's Rugby Sevens is an intermittent, field-based team sport characterised by high-intensity activities and collisions [1]. Two teams of seven players contest matches over two 7-min halves in a tournament format over 2-3 days. Similar to other team sports, a combination of technical, tactical, and physical factors determines success in women's Rugby Sevens [2]. While some of these factors (e.g., tactical awareness, decision making, and passing accuracy) are independent of physical measures, evaluating the relationships between physical-test and match performance could provide helpful information to implement specific training programs for enhancing match performance [2] and refining athlete evaluation.
In a previous study on women's Rugby Sevens across different playing levels, performance in various physical tests (10-m acceleration, 40-m sprint, Yo-Yo Intermittent Recovery Test Level 1, vertical jump) had moderate to large correlations with some match-running activities, including total distance, distance covered >5 m•s -1 , and maximal speed [3]. However, several other measures of match The associations between physical-test performance and match performance in women's Rugby Sevens players as high as possible". Two warm up trials were given, followed by two sets of three jumps separated by two minutes rest. The best jump height (calculated from flight time) recorded by each athlete was included in the analysis. The re-test reliability of the best jump height out of three countermovement jumps was 0.97 (ICC) and 3.6% (typical error) in women's soccer players [11].

Maximal strength
Back squat and bench press exercises were used to evaluate lowerbody and upper-body maximal strength. For the back squat, athletes started from a standing position and were instructed to "lower until the thighs are parallel to the floor and then come up in the starting position". A miss was recorded if participants failed to meet the proper depth or successfully come up in a straight position. For the bench press, athletes started with the arms fully straight, and were instructed to "lower the bar to the chest and press all the way up" while keeping the glutes in contact with the bench. If an athlete bounced the bar on the chest or failed to press the bar all the way up to a fully extended arms position, a fail was given. Each participant completed two warm up sets at sub-maximal intensities. Thereafter, participants were given three attempts to reach their 2-3 repetition maximum (RM) in each lift, with three minutes rest between attempts.
One repetition maximum (1RM) from the lifts was calculated using the formula of Mayhew et al. [12]. ICCs for 1RM testing were ≥0.97 in women's team-sport players [13].

Match performance
Match-running and match-action data were collected during the New Zealand National Rugby Sevens tournament, a two-day tournament between the New Zealand Provincial Unions where each team competes in 5 to 6 matches. Match data were considered for players that completed at least a full 7-minute half of a match; therefore, resulting in 1 to 6 files for each player and a total of 119 files included in the analysis (6 players = 1 match, 2 players = 2 matches, 2 players = 3 matches, 5 players = 4 matches, 7 players = 5 matches, 8 players = 6 matches).

Match running
Match running was measured using GPS units (VX Sport 220, Visuallex Sport International, Wellington, New Zealand) sampling at 10 Hz. The validity and reliability of devices with a similar sampling rate have been investigated previously [14,15]. Each athlete wore the same GPS unit in every match in a fitted vest under the playing jersey. Data were downloaded and analysed post-tournament using the manufacturer's software (VX View software, Sport International, Wellington, New Zealand). Match files were trimmed to include only the time players were on the field. The variables analysed were based on women's Rugby Sevens research [3,4,16] and were described as the frequency of efforts or cumulative distance covered in different speed zones (see Table 1). Sprints were defined as running efforts that required an increase of ≥0.70 m•s -1 within a second and that participant provided written informed consent and ethical approval was granted from the University of Waikato research ethics committee.

Study design
The association between physical-test performance and match performance in women's Rugby Sevens players was examined using a descriptive correlation design. Participants performed a battery of physical tests within the two weeks before a two-day tournament.
Match-running and match-action data were collected as measures of athlete performance using GPS units and video analysis. All tests employed are commonly used in Rugby [6][7][8]. The re-test reliability (intraclass correlation coefficient, ICC) for 10-m, 30-m, and 40-m sprint times in women's Rugby Sevens players using similar equipment was 0.90, 0.95, and 0.96 [8].

Fitness
The 1.2 km shuttle run test, also known as the Bronco test [7], was used as a measure of fitness. The test was performed outdoors, on artificial turf, in running shoes. The protocol consists of a continuous 20, 40, 60 m straight shuttle run, completed five times at maximal intensity (i.e., 20 m and back, 40 m and back, 60 m and back) [9].
Total running time was recorded with a stopwatch. Average running speed was calculated from total time and used for analysis. The ICC for Bronco time was 0.99 in men's and women's team-sport players combined [10].

Match actions
The first author coded match actions using video analysis. The match actions included in the analysis and their operational definitions are presented in Table 2. These measures were chosen to represent different areas of the game in agreement with previous Rugby Sevens studies [6,18]. Intra-rater reliability for the analysis was evaluated by re-analysing 10 random matches four weeks apart and calculating the percentage error, as described by Hughes et al. [19]. Errors observed for all match activities were within a 5% error limit, which was deemed acceptable.

Statistical Analysis
Data were analysed with the Statistical Analysis System (University Edition of SAS Studio, version 9.4, SAS Institute, Cary NC). Pearson correlations between each pair of physical-test variables were derived as a correlation matrix, and the variables were ordered to reveal clusters of similar variables (higher correlations within clusters than between clusters). The same analyses were performed for matchperformance variables.
For measures of match performance that were counts or proportional to counts, the association between each physical characteristic and the measure was analysed with Poisson regression using the generalised linear mixed model procedure (Proc Glimmix) with a log link. This procedure allows modelling of count variables and accounting for repeated match-performance measurements on the same  The qualitative magnitude of the effects was assessed using standardisation, with threshold values for small, moderate, large, very large, and extremely large calculated as 0.2, 0.6, 1.2, 2.0, and 4.0 of the observed between-player SD [20], derived by combining the variances represented by player identity (true differences between players) and the residual (within-player between match variance), and adjusted for small samples [21]. Effect magnitudes for tries were also determined as the factors associated with an increase in the number of tries scored by a team to give the team 1, 3, 5, 7, and 9 extra wins every 10 matches, representing small, moderate, large, very large, and extremely large effects [20]. The factors were estimated using a simulation based on points scored by all the teams in the tournament. There was a mean of 2.7 tries scored per team per match (5 points per try), with a 52% probability of converting a try (2 points per conversion). There were no field goals or penalties. We assumed a team had 10 try-scoring opportunities in a match on the basis of our experience (The resulting magnitude thresholds were not sensitive to the number of opportunities). An opponent team was assumed player. Each physical characteristic (predictor) presented in Table 3 was entered in the model separately as a numeric linear fixed effect to allow estimation of the effect of a two standard-deviation (2-SD) difference in the predictor on match performance [6,20].
The number of the match played by each athlete in the tournament, and the log of total match time (as a fraction of a 14-min match) for each player in each match, were included as numeric linear fixed effects to estimate the tournament trend of the dependent variable and to adjust each player's score to a mean match time, respectively.
Random effects in the model were nominal variables representing player identity (to adjust for between-player differences in means), match identity (to adjust for between-match differences in means), and team identity (to adjust for between-team differences in means).  Physical tests and match performance in women's Rugby Sevens to have an unchanging probability of scoring a try per opportunity equal to 27% (2.7 tries per 10 opportunities). The factor associated with a given increase in wins per 10 matches allowed for the affected team to have a try-scoring probability per trial <27% before the factor was applied (probability = 0.27/√factor), but it increased to >27% after the factor was applied (probability = 0.27*√factor).
Simulations were performed to generate scores in 10,000 matches for the two teams before and after the factor was applied, then wins were scored as 1 and loss or draw as 0.  were also investigated [24,25].  [26]. For these effects, the potential for benefit and harm was also investigated for realistic changes in physical-test measures (less than 2 SD).

Physical tests and match performance
Mean values and between-subjects SD of physical-test scores are presented in Table 3, while means of the dependent variables with the within-player, between-player, and observed SD are reported in Table 1. The within-player SD represents the match-to-match within-player variation, the between-player SD is the true difference between players, and the observed SD is the combination of the within-and between-player SDs representing the observed between-player SD in a typical match.  Effects of a 2-SD difference in physical characteristics on match running and match actions. Data are percent effects with ± 90% compatibility limits, or factor effects with × /÷90% compatibility limits; the observed magnitude and probability of a substantial true effect are also shown. Tables 1-3.
considering the odds ratio of benefit to harm (3700 and 4200, respectively). For these predictors, changes as small as 0.25 SD predicted tries scored that were at least possibly beneficial and with negligible risk of harm, but changes of 0.2 SD were unlikely to be beneficial. Changes in measures of running speed and in bench press smaller than 2 SD were either unclear or at least likely trivial.

Tournament trend
When considering the effects obtained without a physical-test predictor, the measures of match total running and high-intensity changes in speed displayed small to moderate negative trends across the tournament, with adequate precision but only possibly or likely substantial magnitudes. The trend for the match measures of high-speed running ranged from small likely reductions through to small possible increases, but three of the six measures had inadequate precision.
There was a similar pattern for match actions, with seven of the 11 measures lacking adequate precision. The tournament trends sometimes changed substantially with different physical-test predictors in the model, but overall the trends were similar to those without predictors.

Effects of physical-test scores on match performance
The effects of a 2-SD difference in physical-test scores on match running and match actions are presented in Table 4. Compatibility intervals and Bayesian probabilities are shown for a minimally informative prior, since appreciable shrinkage occurred with the weakly informative prior for only one effect, jump height on tries scored. In this instance, the factor effect reduced to 3.1, 90% compatibility limits × /÷2.6, but the magnitude remained large, very likely substantial, and potentially implementable with the odds-ratio assessment of benefit and harm defined by thresholds for match winning.

Match running
Large positive effects were observed for jump height on match maximal speed and distance covered at high intensity, and for accelera-

Match actions
Moderate and small positive effects were observed for jump height and back squat on tries scored when assessed using standardisation, with adequate precision at the 90% and 99% levels respectively; both were likely substantial. Greater positive effects characterised the same predictors for tries scored when assessed via match winning, and the effects became very likely substantial; both effects had adequate precision only at the 90% level, hence the risk of harm was too high (p ->0.005) for a conservative assessment of implementability, but they were potentially implementable when scored were deemed potentially implementable. In Table 4 we have presented the effect of a 2-SD difference in these tests on match performance, representing the difference of moving from a typical low to a typical high value [20]. Achieving such a difference would be unrealistic for players already displaying high test values, but a change of 0.25 SD should be achievable for most players and was still potentially beneficial. There was less evidence for a beneficial effect (small but unclear) of measures of running speed and bench press on match winning; some changes smaller than 2 SD were unclear and therefore worth further investigation for potential benefit. and distance covered at 3.5-5.0 m•s -1 during wins compared to losses in international women's Rugby Sevens [5]. Similarly, in the current study we observed consistently negative correlations between measures of total running and tries scored (Supplementary Table 4).
For most match-running and match-action measures, there was some evidence of small to moderate negative trends over the tournament, likely a result of accumulated fatigue or muscle damage. In line with these findings, professional and state-representative women's Rugby Sevens players displayed small to very large reductions in several match-running measures over a two-day tournament, with greater reductions in state-level players [27]. Both professional and state-representative players also reported a large decline in recovery perception, a large increase in perceived soreness, and had large increases in muscle damage (creatine kinase concentration) over the tournament. No information regarding the tournament trend of match actions in women's Rugby Sevens has been reported in other studies.
Due to the fact the physical tests were undertaken within a 14day period before competition, it is possible that different teams with different training and tapering could have different relationships. To the extent that some of the test measures might be measuring the same underlying construct, the correlations between the measures are similar to reliability correlations, and the measurement error is negligible (in terms of standardisation) only when the correlation is ~0.99 or greater [28]. On this basis, only the 30-m and 40-m speed are effectively the same measure (Supplementary Table 1), and only one needs to be measured. Measures with lower correlations could either be measuring identical constructs with substantial measurement error or they could be measuring somewhat different constructs.
A parsimonious set of physical tests that assess constructs making independent contributions to match performance would be useful for practitioners, but multiple linear regression with a much larger sample size of players is needed to identify them. The small sample size precluded such an analysis. A similar analysis with more players and matches to predict tries scored with the other match-performance measures might identify a parsimonious set of match measures for predicting match performance of individual players. A greater sample size of players and matches is also required to get more evidence about the magnitude of the unclear effects observed in this study, especially those on match winning.

CONCLUSIONS
Ours is the first study to reveal potentially useful relationships between physical-test measures and match performance in women's Rugby Sevens players. In particular, enhancing players' jump height and back-squat performance could increase the likelihood of match success in women's Rugby Sevens. Valuable future research would include multiple linear regression and experimental studies investigating the effect of changes in physical-test measures on match performance to support the promising utility of these findings for enhancing performance in women's Rugby Sevens.